Detecting Defects on a Wafer Using Defect-Specific and Multi-Channel Information

ABSTRACT

Methods and systems for detecting defects on a wafer using defect-specific and multi-channel information are provided. One method includes acquiring information for a target on a wafer. The target includes a pattern of interest (POI) formed on the wafer and a known defect of interest (DOI) occurring proximate to or in the POI. The method also includes detecting the known DOI in target candidates by identifying potential DOI locations based on images of the target candidates acquired by a first channel of an inspection system and applying one or more detection parameters to images of the potential DOI locations acquired by a second channel of the inspection system. Therefore, the image(s) used for locating potential DOI locations and the image(s) used for detecting defects can be different.

BACKGROUND OF THE INVENTION

1. Field of the Invention

This invention generally relates to detecting defects on a wafer usingdefect-specific and multi-channel information.

2. Description of the Related Art

The following description and examples are not admitted to be prior artby virtue of their inclusion in this section.

Inspection processes are used at various steps during a semiconductormanufacturing, process to detect defects on wafers. One important goalfor any wafer inspection system is to suppress nuisance defects.Nuisance defects are detected events which may not be relevant tosemiconductor yields. Nuisance defects may be caused by wafer noise andsystem noise or are physical objects on the wafer. Nuisance defects mayappear anywhere on a wafer. In contrast, some defects of interest (DOI)may appear at only certain locations on a wafer.

Context information for a DOI may be used as prior knowledge for defectdetection. Several approaches that use context information have beendeveloped to detect defects. One such approach uses graphical datastream (GDS) data or design information to find hot spots where defectsmay occur at a higher probability and to inspect defects around the hotspots. Another such approach matches defect background and keeps orremoves matched defects after defect detection.

There are, however, a number of disadvantages to such approaches. Forexample, the first approach works with GDS data. However, GDSinformation may not be available in all circumstances such as for defectengineers in semiconductor fabrication plants. In addition, the user mayneed software that is separated from inspection software to find thedefect areas. Furthermore, the user needs to do pixel-to-designalignment (PDA) and run-time swath-based alignment to overlap care areasaccurately on the images. Since a swath image which covers the entiredie is very large, image distortion may cause alignment inaccuracies. Ifswath-based alignment fails, the locations covered by the swaths willnot be inspected.

The second approach, which is performed after defect detection, cansignificantly slow down inspection if the defect count and types ofnuisance defects are relatively large. In addition, if the defect signalis relatively weak, huge amounts of nuisance defects may be detected.The defect signal may be defined as the maximum gray-level differencebetween an image with a defect and a reference image without the defect.The reference image is spatially-aligned with the defect image and maybe acquired from neighboring dies or from multiple dies on the wafer.Furthermore, if the methods are performed for keeping systematic DOIs,other nuisance removal mechanisms are needed to separate nuisancedefects and randomly-distributed DOIs.

None of these approaches use defect-specific information and amulti-channel system with multiple optics modes to acquire wafer anddefect information.

Accordingly, it would be advantageous to develop methods and/or systemsfor detecting defects on wafers that do not have one or more of thedisadvantages described above.

SUMMARY OF THE INVENTION

The following description of various embodiments is not to be construedin any way as limiting the subject matter of the appended claims,

One embodiment relates to a computer-implemented method for detectingdefects on a wafer using defect-specific information. The methodincludes acquiring information for a target on a wafer. The targetincludes a pattern of interest (POI) formed on the wafer and a knowndefect of interest (DOI) occurring proximate to or in the POI. Theinformation includes a first image of the POI on the wafer acquired byimaging the POI on the wafer with a first channel of an inspectionsystem, a second image of the known DOI on the wafer acquired by imagingthe known DOI with a second channel of the inspection system, a locationof the POI on the wafer, a location of the known DOI relative to thePOI, and one or more characteristics computed from the POI and the knownDOI.

The method also includes searching for target candidates that match thePOI in a die on the wafer or on another wafer. The target candidatesinclude the POI. POI search may be performed in a setup step prior todefect detection. After POI search, micro care areas (MCAs) may becreated based on the position of the known defect relative to the POIposition for each potential defect location. These locations may beprovided for defect detection. In addition, the method includesdetecting the known DOI in the target candidates by identifyingpotential DOI locations based on images of the target candidatesacquired by the first channel and applying one or more detectionparameters to images acquired by the second channel of the potential DOIlocations. Detecting the known DOI is performed using a computer system.

There are several differences between this method and currently usedcontext-based inspection. First, this method does not rely on graphicaldata stream (GDS) data. In addition, a highly accurate care areaalignment may be performed to detect specific defects. The care areaalignment is not performed at the swath image level. It is performed inthe frame image which is the basic image element for detect detection.Furthermore, context and defect-specific information is used duringsetup and defect detection, not after defect detection. In addition, amulti-channel inspection system can separate POI search and defectdetection using different image modes. A different image mode can beobtained by changing spectrum, aperture, polarization, and focus offset.Some image modes may be good for pattern search but may not be good insensing the defects. On the other hand, some image modes may be good forsensing the defect but do not have a good resolution for wafer patterns.The system described herein decouples the pattern search sensitivity anddefect detection sensitivity.

The method described above may be performed as described further herein.In addition, the method described above may include any other step(s) ofany other method(s) described herein. Furthermore, the method describedabove may be performed by any of the systems described herein.

Another embodiment relates to a non-transitory computer-readable mediumstoring program instructions executable on a computer system forperforming a computer-implemented method for detecting defects on awafer. The computer-implemented method includes the steps of the methoddescribed above. The computer-readable medium may be further configuredas described herein. The steps of the computer-implemented method may beperformed as described further herein. In addition, thecomputer-implemented method for which the program instructions areexecutable may include any other step(s) of any other method(s)described herein.

An additional embodiment relates to a system configured to detectdefects on a wafer. The system includes an inspection subsystemconfigured to acquire information for a target on a wafer. The targetincludes a POI formed on the wafer and a known DOI occurring proximateto or in the POI. The information includes a first image of the POI onthe wafer acquired by imaging the POI on the wafer with a first channelof the inspection subsystem and a second image of the known DOI on thewafer acquired by imaging the known DOI with a second channel of theinspection subsystem. The inspection subsystem is also configured tosearch for target candidates that match the POI on the wafer or onanother wafer and to acquire images of the target candidates. The targetcandidates include the POI. In addition, the system includes a computersystem configured to detect the known DOI in the target candidates byidentifying potential DOI locations based on images of the targetcandidates acquired by the first channel and applying one or moredetection parameters to images acquired by the second channel of thepotential DOI locations. The system may be further configured asdescribed herein.

BRIEF DESCRIPTION OF THE DRAWINGS

Other objects and advantages of the invention will become apparent uponreading the following detailed description and upon reference to theaccompanying drawings in which:

FIG. 1 is a schematic diagram illustrating a plan view of one embodimentof a pattern formed on a wafer and the pattern with a known defect ofinterest (DOI) detected in the pattern;

FIG. 2 is a schematic diagram illustrating a plan view of one embodimentof a wafer on which multiple dies and multiple patterns of interest(POIs) are formed within the multiple dies;

FIGS. 2 a-2 d are schematic diagrams illustrating plan views ofdifferent embodiments of a POI, one or more known DOIs occurring near orin the POI, and one or more micro care areas that may be generated forthe known DOIs;

FIG. 3 is a schematic diagram illustrating a plan view of one embodimentof an image, an area within the image that is used to determine one ormore detection parameters, and an area within the image to which the oneor more detection parameters are applied;

FIG. 4 is a flow chart illustrating one embodiment of a method fortemplate and care area setup;

FIG. 5 is a flow chart strafing one embodiment of a method formulti-channel inspection;

FIG. 6 is a block diagram illustrating one embodiment of anon-transitory computer-readable medium storing program instructionsexecutable on a computer system for performing one or more of thecomputer-implemented methods described herein;

FIG. 7 is a schematic diagram illustrating a side view of one embodimentof a system configured to detect defects on a wafer; and

FIGS. 8 and 9 are schematic diagrams illustrating plan views of variousembodiments of illumination and collection schemes that can be used bythe embodiments described herein.

While the invention is susceptible to various modifications andalternative forms, specific embodiments thereof are shown by way ofexample in the drawings and will herein be described in detail. Itshould be understood, however, that the drawings and detaileddescription thereto are not intended to limit the invention to theparticular form disclosed, but on the contrary, the intention is tocover all modifications, equivalents and alternatives falling within thespirit and scope of the present invention as defined by the appendedclaims.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

Turning now to the drawings, it is noted that the figures are not drawnto scale. In particular, the scale of some of the elements of thefigures is greatly exaggerated to emphasize characteristics of theelements. It is also noted that the figures are not drawn to the samescale. Elements shown in more than one figure that may be similarlyconfigured have been indicated using the same reference numerals. Unlessotherwise noted herein, any of the elements described and shown mayinclude any suitable commercially available elements.

One embodiment relates to a computer-implemented method for detectingdefects on a wafer. The embodiments described herein generally includetwo parts: 1) set up, which may include template and care area (CA) setup, and 2) defect detection. During set up, target information iscollected for known defect of interest (DOI) locations and/or vulnerablelocations on a wafer. During defect detection, a wafer is inspectedusing the target information. As will be described further herein, theembodiments apply to both multi-channel and multi-mode inspection aswell as dark field (DF) and any other type of inspection.

The method includes acquiring information for a target on a wafer. Thetarget includes a pattern of interest (POI) formed on the wafer and aknown DOI occurring proximate to (near) or in the POI. The informationfor the target includes a first image of the POI on the wafer acquiredby imaging the POI on the wafer with a first channel of an inspectionsystem, a second image of the known DOI on the wafer acquired by imagingthe known DOI with a second channel of the inspection system, a locationof the POI on the wafer, a location of the known DOI relative to thePOI, and one or more characteristics computed from the POI and the knownDOI. Therefore, the information for the target may include informationacquired with multiple channels (i.e., at least first and secondchannels) of an inspection system. As will be described further herein,the embodiments are particularly suitable for inspection systems thathave multiple channels and uniquely leverage the multi-channelcapability of such inspection systems. The inspection system may befurther configured as described herein.

Given the target information (sample DOIs in specific context), theembodiments described herein may be used to detect all DOIs and suppressnuisance defects on the whole wafer. In addition, since the embodimentsdescribed herein are designed to detect defects in only targetcandidates containing certain patterns, the embodiments described hereinare particularly useful for detecting systematic defects on wafers,which are defects that occur repeatedly in certain patterns on wafersgenerally due to interactions between the pattern and the process usedto form the pattern on the wafer. Therefore, the DOIs may includedefects in the patterns formed on the wafer such as bridges.

The POI may include only a few patterned features in the entire designfor dies formed (or to be formed) on the wafer. In other words, the POIincluded in the target does not include the entire pattern for a dieformed or to be formed on the wafer.

The information for the target may also include a location where the DOImay occur, and the location may be known and unique to the POI location.In this manner, the location of the known DOI is unique relative to thelocation of the POI. In other words, the POI preferably has a uniquespatial relationship with a potential defect location.

In an embodiment, the location of the known DOI is obtained based ondesign data for the wafer. For example, defect locations and vulnerablelocations can be obtained from semiconductor design files. In one suchexample, in set up, the target locations can come from design filesthrough rule-based or pattern-based search.

In one embodiment, acquiring the information for the target includesimporting locations of DOI samples. In another embodiment, the locationof the known DOI and/or vulnerable locations on the wafer are obtainedbased on optical images or SEM images of the wafer. The sources of theselocations may be obtained from inspection results and SEM reviewresults. In this manner, samples of DOI may also be known from certainsources much as e-beam inspection or scanning electron microscopy (SEM)review performed on the wafer.

These locations may be used for grabbing images of the targets. Forexample, in set up, an image patch (template) is created for each detecttype. The location of the image patch is obtained based on the defectlocation or the vulnerable locations. In set up, SEM images can becorrelated to optical images to identity defect locations in the opticalimages. In addition, in set up, optical patch images included inprevious inspection results can be used as the target templates or usedto search for exact defect locations. For example, in one embodiment,the method includes determining the location of the known DOI in anoptical image of the wafer by correlating a SEM image of the known DOIto the optical image of the wafer. In some such instances, the user willwant to know the number of these kinds of defects on the whole wafer.

The information for the target may be generated during setup and mayinclude identifying potential defect locations and computing defectinformation using test and reference images of sample defects. In onesuch embodiment, as shown in FIG. 1, pattern 100 may be formed on awafer and is shown in FIG. 1 as it might be imaged by a high-resolutioninspection system such as an e-beam inspection system or an opticalinspection system. The system may grab two images, one from the targetlocation and the other from a die or wafer on which a POI search will beperformed. The features shown in pattern 100 may be included in a targetdescribed herein since as shown in pattern 102, which is equivalent topattern 100 but with a defect occurring therein, DOI 104 such as abridging defect between patterned feature 106 and patterned feature 108may have been detected in one or more instances of the pattern on awafer. The patterns shown in FIG. 1 are not intended to represent anypattern that may actually be formed on a wafer. Instead, the patternsare intended to show what types of features may be included in the POIof the targets and the types of DOI that may occur therein. The numberof patterned features included in the POI may be selected such thattarget candidates can be identified in images acquired for the wafer orother wafers with a predetermined accuracy. The size of the POI may bealso determined as described further herein.

In one embodiment, acquiring the information for the target includesdisplaying high-resolution images of DOI locations. The images may begenerated from other systems such as SEM review machines or e-beaminspection machines. A “high-resolution” image, as that term is usedherein, is defined as any image acquired at a resolution higher thanthat normally used for wafer inspection. In addition, acquiring theinformation for the target may include providing a graphics userinterface (GUI) to a user. The GUI may display any of the informationthat is acquired for the target.

In one embodiment, acquiring the information for the target includesgrabbing the image of the target on the wafer in known locations of DOIusing an inspection system. For example, during setup, the system grabstwo sets of images, one from the target location in a die and the otherfrom a die on which POI search will be performed. The set of images atthe target location includes test and reference images. The systemaligns one image to another and computes the difference of the twoimages. The user manually marks the DOI location and POI location byreferencing to the test or difference image. The other set of imagesincludes the test and reference images at the corresponding location inthe die for POI search. The system automatically locates the POIlocation in the image of the die for POI search by correlating tworeference images. A template, an image of the POI, may be grabbed fromthe die for POI search when the user specifies the POI location.

In another embodiment, acquiring the information for the target includesgrabbing images of the target on the wafer using multiple channels ofthe inspection system, and the multiple channels include at least thefirst channel and the second channel. In this is manner, the informationfor the target may be acquired, at least in part, by using amulti-channel inspection system. For example, as shown in the method ofFIG. 4, multi-channel inspection system 400 may be used to grab multipleimages 402 of the target on the wafer. In addition, multiple images maybe acquired for both the POI and the known locations of the DOI andincluded in the information for the target. For example, the informationfor the target may include multiple images for the POI grabbed usingmultiple channels of the inspection system.

Grabbing the images may be performed in any suitable manner (e.g.,scanning over the locations of the POI and the known locations of theDOI and acquiring images of the locations during the scanning). Grabbingthe images of the target on the wafer may be performed using aninspection system such as that described further herein, which has thecapability of acquiring a set of multiple types of wafer images of thesame location through multiple channels simultaneously or sequentially.In one embodiment, the inspection system uses different optics modes inthe first and second channels, and the different optics modes aredefined by spectrum, aperture, polarization, scan speed, or somecombination thereof. For example, a multi-channel inspection system maybe used to acquire multiple images of the same location through morethan one channel simultaneously or sequentially with differentperspectives, spectrums, apertures, polarizations, imaging mechanisms,or some combination thereof. Among these images, some images may berelatively good for pattern resolution while other images may berelatively good for defect detection. In any case, the images can bealigned to one another by either hardware or software. For example, inone embodiment, the images acquired by the first and second channels arespatially registered to each other by image sensor calibration andalignment algorithms applied on the images, which may be performed inany suitable manner.

The images included in the target information may also include imagesgrabbed by the inspection system and/or grabbed images that have beenmanipulated in some manner. For example, the first image of the POI maybe acquired by imaging the POI on the wafer with one or more of themultiple channels of the inspection system and then processing thegrabbed images, e.g., to generate difference images that are used as thefirst image(s) or to create templates from the grabbed images that areused as the first image(s), etc. In one embodiment, the method includescreating a template for the POI and modifying the template by changingthe size of the template or flipping, rotating, or processing thetemplate. The template shape may be a square or rectangle and its sizemay be smaller than the image acquired by an inspection system.

In another embodiment, acquiring the information for the target includesgrabbing images of the POI with multiple channels of the inspectionsystem, determining which of the grabbed images is best for patternsearching, and designating one of the multiple channels with which thebest of the grabbed images for the pattern searching was grabbed as thefirst channel. For example, as shown in the method of FIG. 4, multipleimages 402 may be used to determine image 404 that is the best forpattern search. In addition, during set up, the method may includesearching the potential defect locations using one or more image types,which have the best image resolution among all images acquired. Theseimage types may be different from the image types used for defectdetection.

In some embodiments, acquiring the information for the target includesgenerating additional images of the wafer at and proximate to the knownDOI with multiple channels of the inspection system, determining whichof the additional images is best for pattern searching, and selectingthe POI from the additional image that is determined to be the best forthe pattern searching. For example, during set up, multiple imagepatches may be acquired at or near sample defect locations from one die.As shown in the method of FIG. 4, image 404 that is the best for patternsearch may be used to identify a suitable POI from the patterns on thewafer that are included in that image. In some instances, the user maydefine the POI in the image that has the best resolution for patternsearch.

In one embodiment, acquiring the information for the target includesdetermining a similarity between a template for the POI and an image ofthe target acquired by imaging the target on the wafer with the firstchannel and determining a uniqueness of the POI relative to otherpatterns proximate to the POI (i.e., the uniqueness of the POI withrespect to its surroundings). For example, during template grabbing, acorrelation value between images from the target die and the die for POIsearch may be calculated and saved for POI search. The template isselected to find the DOI location uniquely. A metric that measuresuniqueness of the template may be calculated. For example, the ratio ofthe second highest peak and the highest peak values among correlationvalues for all locations in the image can be used as the uniquenessmetric. The user can adjust the template location according to theuniqueness value.

In one embodiment, the POI has a width and a height that are shorterthan a width and a height, respectively, of dies formed on the wafer andthe other wafer. For example, FIG. 2 shows a wafer on which multipledies are formed and multiple POIs are formed within each of the multipledies. In particular, wafer 200 may be printed during a wafer fabricationprocess (e.g., lithography) with dies 202 in a certain layout. A firstPOI 204 may be located in a first position in the dies. For example,first POI 204 may be located in the upper left hand corner of the dies.In addition, as shown in FIG. 2, POI 204 has a width that is less than awidth of the dies and a height that is less than a height of the dies. Asecond POI 206 is located in a second position in the dies differentthan the first position of the first POI. Furthermore, as shown in FIG.2, POIs 204 and 206 may have different dimensions from each other. Forinstance, since POIs 204 and 206 include different DOIs detected indifferent patterns, the two POIs may have different dimensions that aredetermined based on the DOIs located in the different patterns. Inaddition, as shown in FIG. 2, POIs 206 have a width that is less than awidth of the dies and a height that is less than a height of the dies.Furthermore, POIs can be partially overlapped.

In one embodiment, the pattern included in the target is preferablyresolvable by an inspection system. The embodiments described hereinwill not work in non-pattern areas and will not work for randomlydistributed defects.

In another embodiment, acquiring the information for the target includesgrabbing templates for all known DOIs in one die, on the wafer or theother wafer, in which searching for target candidates as describedfurther herein is performed with at least the first channel of theinspection system. The locations of these templates may be obtained bycorrelating the images of the targets with the images generated from thedie for POI search. There may be many types of targets. One template maybe grabbed for each type and for each channel. For example, as shown inFIG. 4, for an identified POI, template creation 410 may be performed tocreate POI template 412 for the identified POI. The template may becreated in any manner described herein. Acquiring the information mayalso include defining the template location and size. In addition,acquiring the information may also include defining an area where one ormore parameters may be determined for defect detection.

All templates may be grabbed from the same die for POI search. Due torelatively small variations in wafer structures, the image intensitiesof wafer patterns are sometimes substantially different across a wafer.This difference is referred to as color variation. Color variation ismuch smaller within a die than across a wafer. To ensure substantiallyhigh quality for POI search, all templates may be grabbed from one dieand POI search may be performed on the die from which the templates aregrabbed.

In one embodiment, acquiring the information for the target includesgrabbing images of the known DOI with multiple channels of theinspection system, determining which of the grabbed images is best fordetecting the known DOI in the target candidates described furtherherein, and designating one of the multiple channels with which the bestof the grabbed images was grabbed as the second channel. For example,from among multiple images 402 shown in FIG. 4, the image that is bestfor defect detection may be determined. The channel(s) that were used tograb those image(s) may then be designated as the defect detectionchannel(s).

The images of the potential DOI and POI locations that are grabbed maybe displayed to the user. The user can refine target candidates byreviewing images of POI and potential DOI locations and their similarityvalues. The POI locations are saved for defect detection. The targetinformation and target candidate locations may be provided to defectdetection.

The characteristics of POI and DOI may also be calculated. This targetinformation will be saved for POI search which will be described later.For example, in one embodiment, the one or more characteristics includeone or more characteristics of the known DOI. In one such example,defect information may be determined using test and reference images ofsample defects. In particular, a reference image may be subtracted froma test image to generate a difference image, and the one or morecharacteristics of the known DOI may be determined from the differenceimage. In one such embodiment, the one or more characteristics includesize, shape, intensity, contrast, or polarity of the known DOI. Defectsize, shape, contrast, and polarity can be calculated using a differenceimage for the target. Intensity can be calculated from the test image ofthe target.

In the method shown in FIG. 4, from among multiple images 402, targetinformation creation 406 may be performed. In an additional embodiment,the one or more characteristics include one or more characteristics ofthe known DOI determined from the second image acquired with the secondchannel, in this manner, target information creation may be performedusing at least the image(s) that has or have been designated as the bestfor defect detection. For example, using the image(s) that has or havebeen determined to be the best for defect detection, one or morecharacteristics of the DOI such as those described herein may bedetermined, in this manner, the method may include determining defectinformation from the image types used for defect detection. Other targetinformation 408 may also be created using multiple images 402 or thetarget information created in step 406. In this manner, different typesof information may be determined for the target using any of the imagesthat are grabbed for the wafer.

Different targets can share some of the same target information. Forexample, two DOIs may be located in or proximate to the same POI. Thepotential locations for these two DOIs can be defined relative to thePOI location and can be identified by searching for the POI. In anotherexample, two DOIs have the same characteristics, such as polarity. Adefect polarity is defined by its gray level, which is either brighteror darker than its background.

The method may also include searching all POI locations from one die todetermine if a DOI is in or near any of the POI locations. The potentialDOI locations corresponding to these POI locations are referred to astarget candidates. In this manner, the method may include searching forall target candidates (or potential DOI locations) in a die. The samepattern occurs at these locations, but DOI may or may not occur at theselocations. Only if a DOI is detected at a location are the pattern andthe defect an actual target. In some embodiments, the method includessearching an image of a die on the wafer or the other wafer for the POIby determining if a template for the target correlates with differentportions of the image of the die. For instance, an inspection system maybe used to grab images for an entire die and run a correlation (such asa normalized cross correlation (NCC)) between the template and images tosearch for the POI locations. The locations passing a correlationthreshold value are target candidates. The user has an option to refinetarget candidates manually. The POI locations obtained from POI searchare saved and will be used during defect detection.

As semiconductor design rules shrink, there is a higher chance forcertain wafer structures to cause a defect. When those wafer structuresare identified using design data such as graphical data stream (GDS)data, the structures are generally referred to as “hot spots,” Morespecifically, “hot spots” may be identified by using GDS data todetermine which wafer structures may (hypothetically) cause defects onthe wafers. There may be different types of hot spots in one die, andthe same type of hot spots may be printed at multiple locations in adie. Defects produced at hot spots are generally systematic defects andusually have weaker signals than surrounding noise making themrelatively difficult to detect.

Hot spots are therefore different than the targets described herein inthat the targets described herein are not identified as wafer structuresin GDS data that may cause defects. Instead, the targets are identifiedusing one or more actual wafers on which the wafer structures have beenformed. For example, e-beam inspection or e-beam review may be used tofind targets in substantially local areas. Because the throughput ofe-beam inspection and e-beam review is generally substantially low, ittypically cannot be used to inspect an entire wafer. However, theembodiments described herein can be used to, given a location of atarget such as one found by e-beam inspection, determine how many targetcandidates are formed on the entire wafer and how many DOIs appear atthese target candidates. In this manner, given a sample defect location,the method may determine how many of this kind of defect are on thewafer.

The embodiments described herein are, therefore, substantially differentthan methods that detect defects using GDS-based inspection. Forexample, GDS-based methods try to catch any type of defect and performpixel-to-design alignment to generate images for run-time, swath-basedalignment. In contrast, the methods described herein use an image of asample DOI to find all defects of the same type on the entire wafer. Thesample DOI can be from SEM review, e-beam inspection, or anotherinspection or defect review results file. During inspection, each POIlocation may be adjusted by correlating a template to the wafer image.Therefore, the two methods are not identical in that methods that usehot spots look for all possible defects while the methods describedherein took for only specific known defects.

Setup of the methods described herein may also include any othersuitable steps such as optics selection, which may be performed based ona known defect location. Some methods may also include inspecting anyone target or one type of target with multiple optics modes of aninspection system. Optics modes are parameter configurations ofwavelength, aperture, focus, light level, and the like for inspectionsystems. Such a method may include selecting one or more parameters forthe multiple modes. In this mariner, the method may include setting upmore than one mode for the target-based inspection. Such a method mayinclude using the best mode for defect signal to select DOI fromdifferent dies and collecting target information from one die.Collecting the target information may include grabbing defect images atthe die locations obtained in the first step and performing inter-modeimage alignment to find the corresponding template in another mode thatis best for POI search. The method may then include finding all targetcandidate locations in one die using the search mode. The locations canthen be viewed or revised based on image patches grabbed at theselocations. The detection recipe may then be setup with the best mode fordefect signal. Inspecting the target candidates may be further performedas described herein.

In comparison to using a single channel inspection system, which limitsthe inspection to using the same type of image for both patternsearching and defect detection, the embodiments described herein can usedifferent types of images generated by different channels of aninspection system for 1) identifying the target location on the waferand 2) performing defect detection at the target. Using different typesof images for different functions during inspection provides a number ofadvantages to the embodiments described herein. For instance, some typesof images may be good for wafer pattern sharpness while others may begood for defect signal. In one such example, a bright field (BF) modemay provide the best wafer image resolution, which is good for patternsearching. In addition, a dark field (DF) mode may provide the bestdefect signal and may be good for defect detection. In this case, twoscans are required to obtain two types of images, and alignment betweenthe two types of images is required. The embodiments described hereinprovide such capability by decoupling the pattern search sensitivity anddefect detection sensitivity.

The method also includes searching for target candidates on the wafer oron another wafer. For example, as shown in FIG. 4, POI template 412 maybe used for POI search 414. The target candidates include locations ofthe POI on an entire die). There may be many locations with same type ofpattern as a target. The same type of defect may occur at some of theselocations. In order to detect all defects, these locations are searchedand reported. To search these locations, the system may visit each pixelon the die and calculate a value for the similarity between the templateand a pattern around the pixel on the die. If the similarity value islarger than a threshold defined at the template grab, the location ofthe pixel is marked as a POI location. The target candidate locationscan be calculated by adding a position offset from POI to targetcandidate location.

In one embodiment, the first channel, at least in part, defines the bestoptics mode for image matching of the images of the target candidates tothe first image or a template for the POI. In this manner, searching forthe target candidates may be performed using the first image(s) acquiredfor the target using the best optics mode for image matching of theimages of the target candidates to an image or a template for the POI.For example, the image of a POI, called a template, may be used tosearch entire logic areas to find all locations of potential defects bymatching the templates to the wafer images, and the image that has thebest pattern resolution may be used in POI location search. In thismanner, POI searching may be performed with images obtained in an opticsmode that is best for image matching. Acquiring target information anddefect detection as described further herein may be performed usingimages obtained with different optics modes. For example, in oneembodiment, imaging the target on the wafer is performed using a firstoptics mode, and the images of the target candidates used for detectingthe known DOI in the target candidates are acquired using a secondoptics mode different than the first optics mode. Inter-mode imagealignment may be performed between two optics modes.

In one embodiment, acquiring the information for the target andsearching for the target candidates are performed using the inspectionsystem (i.e., the same inspection system). In addition, acquiring thetarget information and searching for the target candidates may beperformed with the inspection system in a setup step before defectdetection. For example, the same inspection system should be used fortemplate grab and POI search. Alternatively, acquiring the informationfor the target and searching for the target candidates are performedusing different inspection systems of the same type. In this manner,acquiring the information for the target and searching for the targetcandidates may be performed using a different inspection system of thesame type as the inspection system. In another embodiment, acquiring theinformation for the target and searching for the target candidates areperformed in different dies on the wafer or the is other wafer, andsearching for the target candidates is performed in one die on the waferor the other wafer using one or more templates for the targetcandidates.

In one embodiment, the target candidates can come from other sources,such as GDS-based pattern search. In these cases, the target-basedinspection only needs to grab templates and compute the targetinformation. Image-based search for POIs can be Omitted.

In one embodiment, the method includes determining one or moreparameters of a care area for the target-based inspection. In anotherembodiment, acquiring the information for the target includes specifyingsize, shape and location of care areas, size, shape and location oftemplates, and area where the one or more characteristics are determinedin the images to which one or more detection parameters are applied (theimages used for defect detection). For example, a micro care area (MCA)may be defined based on the locations of the target candidatesidentified in the searching step. In addition, the target locations cancome from design files through rule-based or pattern-based search, andthese locations can be used to create MCAs. A “care area” is a set ofconnected image pixels where defect detection is performed. Since thetarget candidate location is substantially accurate, an MCA can bedefined around the location. An MCA size of a location around the targetmay be defined by a user with the help of a computer GUI. The size ofthe MCA can be, for example, 5 pixels by 5 pixels. In this manner, themethod may include determining one or more parameters of a care areabased on results of the searching step described herein. For example, asshown in FIG. 4, the method may include determining care areas 416 basedon POI search 414. An MCA is created for each target candidate. Inaddition, as described further herein, MCAs may be generated to coverone or more of the potential DOI locations.

In this manner, during inspection, POI locations may be searched bycorrelating a template and the image generated for inspection. MCAlocations may be corrected with the POI search result. Duringinspection, these locations are examined for any DOI activity. Forexample, defect detection may be performed by the computer system withinthe MCAs. MCAs serve as only approximate locations of defects, and theexact defect locations can be identified at run time based on the MCAsand the templates (image patches). The purpose of this step is to findapproximate locations of potential defects, reduce the care areas forknown DOIs and significantly exclude the areas that do not contain DOIsof known types and contain nuisance defects. Since the embodimentsdescribed herein use defect specific information, DOI detection andnuisance suppression are more effective.

For each type of defect, one type of MCA around the locations that matchthe template may be generated. For example, for each type of defect, onetype of MCA may be generated around the defect location based on a POIlocation. FIGS. 2 a-2 d show various relationships between a pattern ona wafer, a POI in the pattern, one or more DOIs located in and/or nearthe POI, and one or more MCAs that can be generated for each of theDOIs. For example, as shown in FIG. 2 a, POI 210 may be located inpattern 212. The image of POI 210 shown in FIGS. 2 a and 2 c-2 d is thePOI as it may appear in a template for the POI. As shown in FIG. 2 a,DOI 214 may be located near POI 210, but not necessarily in POI 210, MCA216 may be positioned around and centered on the location of the DOI. Ina similar manner, as shown in FIG. 2 b, POI 218 may be located inpattern 220. The image of POI 218 shown in FIG. 2 b is the POI as it mayappear in a template for the POI. DOI 222 may be located in POI 218. MCA224 may be determined around and centered on the location of the DOI.One POI can be associated with more than one DOI. For example, as shownin FIG. 2 c, DOI 226 may be located in POI 210 while DOI 228 may belocated near POI 210, but not necessarily POI 210. MCA 230 may bepositioned around and centered on the location of DOI 226, while MCA 232may be positioned around and centered on the location of DOI 228.Therefore, each of the MCAs may be associated with only one of the DOI.However, an MCA may be associated with more than one DOI. For example,as shown in FIG. 2 d, MCA 234 may be generated for both DOI 226 and 228.POI and MCA shapes are not limited to a square or rectangle. Thepatterns shown in FIGS. 2 a-2 d are not intended to represent anypattern that may actually be formed on a wafer.

In one embodiment, the method includes determining a care area locationby correlating a template image for the POI and the images used for thetarget candidates acquired by the first channel and applying the carearea location to the images acquired by the second channel of thepotential DOI locations. In this manner, the POI search may be performedusing the images acquired with the best resolution or that have beendetermined to be best for pattern matching and the care area locationscan be applied to the images determined to be best for defect detection.In addition, POI search and defect detection may be performed with twodifferent wafer scans. The MCAs generated during POI search may serve asonly approximate locations of defects during an inspection process. Theexact defect locations can be identified by correlating the templatewith the image acquired with the best channel for pattern matching.Furthermore, the MCAs may not be accurately aligned with the potentialdefect locations. As such, during defect detection, a template may becorrelated with the image acquired by the best channel for imagematching to refine the MCA location. Such an embodiment may also includecorrecting wafer stage uncertainty. Then, defect detection can beperformed within these MCAs as described further herein.

In one such embodiment shown in FIG. 5, the method includes imageacquisition 500, which may be performed as described herein using amulti-channel inspection system, which may be configured as describedfurther herein. In this manner, image acquisition 500 may producemultiple images 502 generated by multiple channels of the inspectionsystem. These images acquired from multiple channels are aligned to eachother by the imaging system. As further shown in FIG. 5, care areaplacement 504 may be performed using at least one of multiple images502, care areas 506, and POI template 508. For example, usinginformation about the care areas, the POI template, and the image(s)that are best for pattern matching, the care area(s) may be placed inthe image(s) that are best for defect detection. More specifically, oncethe POI template has been matched to one or more images that are bestfor pattern matching, information about where the POI template matchesthose one or more images as well as care area location relative to thePOI location may be used to place a care area in another of the one ormore multiple images that was or were generated using the channel(s)that is or are best for defect detection. As such, cross-channelinformation may be used to place care areas in images generated by fewerthan all of the channels of an inspection system.

As further shown in FIG. 5, information about the care area placement aswell as one or more of multiple images 502 may be used for defectdetection 510. For example, once a care area has been placed in an imageto be used for defect detection, one or more defect detection parametersmay be applied to the image based on where the care area is located inthe image. Such defect detection may be performed as described furtherherein. In addition, in some embodiments, other target information 512may be used for defect detection 510. For example, as described furtherherein, information about the known DOI may be used for defectdetection. As shown in FIG. 5, defects 514 may be detected by defectdetection 510. The method shown in FIG. 5 may include any other step(s)described herein.

In this manner, target-based inspection may include only using imagepixels in the care areas for the target candidates and as such, imagepixels may not be used for non-target candidates on the wafer andinspection may not be performed for non-target candidates. Therefore,the embodiments described herein may be different than most inspectionmethods, which typically involve using image pixels in entire images.Such currently used methods are advantageous for a number of use casessuch as detecting any defects that might be present in any locations onthe wafer. However, these methods may not be able to find any DOI if thewafer noise is substantially high and DOI signal is relatively weak.Since the embodiments described herein are performed for only specificDOI that are present in only specific target candidates on a wafer, theembodiments are capable of detecting DOI that have relatively lowsignal-to-noise ratios with substantially high throughput whilesubstantially suppressing nuisance defects in other areas. In addition,if there is only one location for a specific DOI, a POI search (setupstep) can be bypassed.

In addition or alternatively to determining one or more parameters of acare area for the target, during setup the method may includeidentifying potential locations of target candidates on the wafer. Forexample, the positions of the targets within a die that will be formedon the wafer and information about the layout of the dies on the wafermay be used to identify potential locations of the target candidates onthe wafer and therefore potential locations of the DOI on the wafer.

The method further includes detecting the known DOI in the targetcandidates by identifying potential DOI locations based on images of thetarget candidates acquired by the first channel and applying one or moredetection parameters to the images acquired by the second channel of thepotential DOI locations. In this manner, during inspection,multi-channel images are used for different purposes. In particular, theimage type that is best for pattern search may be used to findsubstantially accurate locations of the MCAs. As such, the exact defectlocation can be found by applying pattern matching around the MCA usingthe template that is good for pattern matching. The defect informationis used to determine whether a targeted defect exists at the specificlocations. The image type best for defect detection is preferably usedto detect defects. In particular, within the MCAs, the image that isbest for defect detection is used to detect defects.

Detecting the DOI may include identifying the exact locations of thetarget candidates and checking whether the known DOI exists at thelocations based on the defect information. More specifically, duringinspection, MCAs, templates, and defect information generated duringsetup may be sent to a computer system such as that described furtherherein. For example, in one embodiment, the detecting step includesproviding the information for the target to a defect detection modulesuch as a computer system described herein in order to identify thepotential DOI locations accurately. In this manner, the template may beused to find the exact location of the target candidates. For example,in one embodiment, the detecting step includes identifying the potentialDOI locations in the images of the target candidates by correlating atemplate obtained during setup and the images of the target candidatesobtained during defect detection.

The template may be correlated with the images acquired for the targetcandidates within a range using any suitable correlation such as NCC.This range is determined according to the wafer stage uncertainty andthe inspection pixel size. A typical value is 20 pixels. The location ofthe pixel corresponding to the maximum NCC value is selected as the POIlocation. The target candidate location can be calculated based on thedefect location relative to the POI location. In this manner, duringinspection, the embodiments described herein find substantially accuratetarget candidate locations using image matching. The image types usedfor search during inspection are the same types used for search duringset up.

In the case where multiple POI locations of the same target appear inone image, POI search is performed for one location and the offset fromthe approximate MCA location to the true MCA location is calculated.This offset is applied to other approximate MCA locations in this image.It is not necessary to search for all POI locations.

Since the embodiments described herein perform target-based alignment tosubstantially accurately locate all potential defect locations, theembodiments described herein are advantageous over swath alignment-basedapproaches which may be used in design-based methods. A swath is the rawimage generated by a time delay integration (TDI) sensor that covers anentire die row. Swath-based alignment correlates the care areas to theswath image. Swath-based alignment may fail for a relatively smallpercentage of the inspection data. If such misalignment happens, thewhole swath will not be inspected or a substantial amount of nuisancedefects will be detected and reported due to misaligned inspection data.However, the embodiments described herein will be immune to suchalignment issues because the target-based correlations described hereinare performed locally.

Applying one or more detection parameters to the images for the targetcandidates may be performed in any suitable manner. For example, in someembodiments, applying the detection parameter(s) includes generatingdifference images using the images of the potential DOI locations and areference image, calculating a noise measure and a threshold, andapplying a threshold to signals in the difference images. In anotherembodiment, the method includes determining one or more characteristicsof difference images proximate to the potential DOI locations, andapplying the detection parameter(s) includes applying a threshold to oneor more values of the one or more characteristics of the differenceimages. The reference image may be, for example, an image of thepotential DOI location in a die in which the DOI has not been detected,a median image of multiple dies, or a template acquired at setup. Forexample, in one embodiment, the images of the potential DOI locations towhich the detection parameter(s) are applied include images generatedusing a reference image and a test image, and the reference image is atemplate for the POI. In this manner, the reference image may not be animage acquired during inspection. In other words, the reference image isnot limited to an image acquired during inspection. In another example,a location of a non-defective target candidate may be identified on thewafer and an image may be acquired at the location on the wafer usingthe inspection system. This image may be subtracted from the imageacquired at the location of another target candidate to generate adifference image, and a threshold such as that described herein may beapplied to the difference image. Any signals in the difference imageabove the threshold may be identified as a defect or a potential defect.Detecting the known DOT is performed using a computer system, which maybe configured as described further herein.

The method of using a template as the reference image is advantageous incertain situations. For example, if the number of systematic defects issubstantially high, a majority of the dies on a wafer will be defective.If two defects appear at the same die location on two neighboring dies,the difference image between images of these two dies may not reveal thedefect. It is substantially likely that a median of multi-die images isdefective. Thus, the median image cannot be used as the reference image.The reference image may be determined at setup and verified as defectfree. Therefore, it can be used during inspection.

In some embodiments, the method includes determining the detectionparameter(s) based on the information for the target. For example, thedetection parameter(s) (or the defect detection algorithm) may be noiseadaptive. That is, if noise is relatively high in the images acquiredfor the target, the inspection sensitivity may be set relatively low.Otherwise, the inspection sensitivity may be set relatively high. Theinspection sensitivity may be set relatively low by selecting arelatively high threshold that is applied to difference images for thetarget candidates. In contrast, the inspection sensitivity may be setrelatively high by selecting a relatively low threshold that is appliedto difference images for the target candidates. In addition, in anotherembodiment, the method includes determining the detection parameter(s)separately for each target type based on images for each target type,respectively. Therefore, since the methods can be used for differenttypes of targets, different thresholds can be used for detecting defectsin different types of target candidates. For instance, a first thresholdmay be used for detecting a first known DOI in a first type of targetcandidate, and a second, different threshold may be used for detecting asecond, different known DOI in a second, different type of targetcandidate.

The same detection parameter(s) may be used to detect defects in each ofthe target candidates having the same target type. However, in anotherembodiment, the method includes determining the detection parameter(s)separately for each of the target candidates for which detecting theknown DOI is performed based on the images of the target candidates,respectively. In this manner, the detection parameter(s) may bedetermined on a target candidate-by-target candidate basis. For example,once a potential target candidate or potential DOI location has beenidentified, the standard deviation of the difference image in a localarea may be determined. The threshold may then be determined asthreshold=Mean+G+K*StandardDeviationOf (difference in a local area),where Mean is the average value of the difference image in a local areaand G and K are user-defined parameters. G and K are signed values.However, the threshold for each target candidate may be determined inany other suitable manner.

The DOI information may also be used to determine whether a known DOIexists at the potential DOI locations. For example, in an additionalembodiment, the one or more characteristics include characteristic(s) ofthe known DOI such as any of those described above, and applying thedetection parameter(s) includes applying a threshold to one or morevalues of the characteristic(s) determined from the images of thepotential DOI locations. In one such example, if a characteristic of theknown DOI such as polarity is consistent from DOI to DOI, then detectingthe DOI may include thresholding the values for the characteristic. Suchpolarity-based thresholding can be applied to the image acquired for thetarget candidate that correlates to the template or a difference imagegenerated as described above for the target candidate. Thresholding ofthe defect characteristic(s) may be used in combination with otherthresholding described herein (e.g., thresholding the signals in thedifference images). Using defect characteristics such as polarity anddefect size in this manner can also be helpful for suppressing nuisancedefects.

In a further embodiment, the images of the potential DOI locations towhich the detection parameter(s) are applied are images of care areassurrounding the potential DOI locations, and the care areas aredetermined based on a size of the known DOI occurring proximate to or inthe POI. For example, the size of the image that is acquired at roughlythe location of the target candidate may be relatively large to be surethat an image is actually acquired for the target candidate. In one suchexample, area 300 shown in FIG. 3 may be roughly the size of the imagethat was acquired at the target candidate. In addition, area 300 may bethe size of the difference image generated for the target candidate. Thelocation of the target candidate within that image may then bedetermined using correlation as described above. An area known to belarger than the target candidate may then be used to determine athreshold on a target candidate-by-target candidate basis as describedabove. For example, as shown in FIG. 3, area 302 within area 300 may beused to determine the threshold for the target candidate. The thresholdmay then be applied to an area slightly larger than the area of theknown DOI. For example, as shown in FIG. 3, area 304 within area 302 maybe the area to which the threshold is applied, and area 304 may beslightly larger than the area of the known DOI. In one such example, theportion of the image used to determine the threshold may be about 64pixels by about 64 pixels while the area to which the determinedthreshold is applied may be about 5 pixels by about 5 pixels, dependingon the size of the known DOI. Reducing the size of the difference imageto which the threshold is applied reduces the possibility that noise inthe image will be mistakenly identified as a potential DOI. In addition,using such a substantially small area as the care area to which thethreshold is applied allows the use of a substantially low thresholdwithout detecting overwhelming nuisance defects. For this reason, thecare area used in this embodiment is referred to as a micro care area orMCA. In contrast, many currently used inspection methods that userelatively low thresholds for substantially sensitive inspection detecthuge amounts of nuisance defects that have to then be separated from theDOIs.

In one embodiment, the method includes selecting one or morecharacteristics of the target, selecting the detection parameter(s), anddetermining one or more parameters of a care area such that nuisancedefects other than the known DOI are not detected in the targetcandidates (e.g., only locations in which the known DOI likely occur areinspected). For example, the care areas may be reduced to include areasonly for known DOIs and to substantially exclude the areas that do notcontain known DOIs and only contain nuisance defects. In particular, thecare areas can be defined around the locations where known DOI mayoccur. Therefore, noise outside of the care areas can be completelyignored. In addition, since the image of the target or a template can beused to find substantially exact locations of the target candidates, thecare areas can be made substantially small. The care areas used in theembodiments described herein may also be substantially smaller thanother currently used care areas since other methods do not have amechanism to locate target candidates substantially accurately. The moreaccurate the target candidate locations can be determined, the smallerthe care area that can be used and the less nuisance defects will bedetected. In addition, the embodiments described herein can detectsystematic defects by refining care area locations that originate fromdesign data.

Although the embodiments are described herein with respect to searchingfor target candidates and detecting the known DOI in the targetcandidates, it is to be understood that the embodiments described hereincan be used to search more than one type of target candidate and todetect DOI in more than one type of target candidate. For example, theremay be multiple types of bridge defects on a wafer, or the same type ofbridge may occur in different wafer structures. These bridges can betreated as different types of targets. The embodiments described hereinmay include using the information about these types of targets to searchan entire die for any other instances of the target candidates. MCAs aredefined around these target candidates and their locations are refinedduring inspection. Defect detection may be performed for each instanceof the target candidates. In this manner, the embodiments describedherein may be used to inspect target candidates across an entire wafer.

In one embodiment, none of the steps of the method are performed usingdesign data for the wafer or the other wafer. In other words, designdata for the wafer or the other wafer is not required for any step ofthe method. Therefore, the embodiments described herein are advantageousin that they do not require design data. Instead, inspection imagesother than GDS information are used. As such, GDS availability is not anissue. In contrast, methods that use hot spots require design data inorder to be performed. Such methods sometimes also need support fromsomeone (e.g., a customer) with design knowledge. However, since theembodiments described herein do not require any design data, any usercan perform the inspection, which is a significant advantageparticularly since the design data may not be available in allinstances.

In one embodiment, each step of the method independently may use designdata for the wafer or the other wafer. For example, the embodimentsdescribed herein can work with information provided from design data.For example, a design engineer may indicate a wafer structure that isprone to a bridge defect and would like to monitor the location. Targetinformation can be generated, and a search can be performed in a die tofind all target candidates having the same pattern as the target. Defectdetection can be performed in these target candidates to find othertargets on this wafer or other wafers. In another embodiment,design-based pattern search can be performed to find all targetcandidates on a die. The embodiments described herein can generatetarget information, skip the image-based search and perform defectdetection at these target candidates.

The embodiments described herein may also be performed as design-basedinspection. For example, all target candidate locations can be used ashot spot locations. Design-based inspection creates relatively smallcare areas around hot spots and performs pixel-to-design alignment torefine care area locations. Then, defect detection is performed at hotspots.

Signals in the images of the target candidates corresponding to theknown DOI may be approximately equal to or weaker than signalscorresponding to nuisance defects on the wafer. For example, a regularinspection may involve performing defect detection in inspection careareas that cover most of the area of the die. In situations in whichsignals for DOIs are much weaker than false (nuisance) defects,overwhelming false defects can be detected by existing approaches. Forexample, in order to detect defects with relatively weak signals, asubstantially sensitive inspection may be performed, which also detectsmany nuisance defects. The nuisance count may be more than 99% of thetotal detected events. It is substantially difficult to find DOI amongsuch massive amounts of nuisance defects. For example, feature vectorsand defect attributes may be computed for each defect from images andused in defect classification. However, sometimes, the DOIs cannot beseparated from nuisance defects because these two types of events canoccupy the same areas in feature vector and attribute space. Therefore,extra information must be used to solve this problem. Furthermore, if aless sensitive inspection is used, the nuisance rate can besignificantly reduced but DOI may also be lost i.e., undetected).

In contrast, the embodiments described herein suppress huge amounts ofnuisance defects. For example, the embodiments described herein useinformation that targets on specific DOI and is very relevant for defectdetection. Classification approaches remove nuisance defects afternuisance events are detected. The embodiments described herein attemptto prevent nuisance events from being detected. More specifically, theembodiments described herein allow a highly sensitive inspection to berun while controlling the nuisance defect count by inspecting the waferin areas (i.e., the target candidates) in which the known DOI willlikely appear. In other words, using substantially accurate defectlocation information as described herein is a major contributor tonuisance suppression. In this manner, the embodiments described hereincan achieve significant nuisance defect suppression for known DOIs withrelatively weak signals in repeating structures. Thus, the embodimentsdescribed herein can detect DOIs and suppress nuisance defects moreaccurately.

The embodiments described herein may be complementary to any otherinspection that may also be used to inspect the wafer. For example, inanother embodiment, the method includes acquiring other images for thewafer or the other wafer and using the other images to detect otherdefects on the wafer or the other wafer. In one such example, for otherareas (e.g., areas other than the care areas), a regular inspection maybe setup and run as usual to detect randomly-distributed defects and theembodiments described herein may be run to detect systematic defectswith relatively weak signals. In addition, detecting the known DOIs asdescribed herein and regular inspection can be performed in one testthereby providing significant throughput advantages. For example, theembodiments described herein may be used to detect known DOIs withrelatively weak signals and can be run in parallel with any generalinspection approach.

The embodiments described herein may also be used for specific nuisancedefect removal. For example, the embodiments described herein may beperformed as described herein but instead of being performed for a knownDOI, the embodiments can be performed for a known systematic nuisancedefect. The known nuisance defects can be defined as removal targets. Adon't care area can be defined for removal targets. The embodimentsdescribed herein can search removal target candidates on a die, define adon't care area around the removal candidate and not perform defectdetection in the don't care area. Thus, this type of nuisance defectwill not be detected.

Each of the embodiments of the method described above may include anyother step(s) of any other method(s) described herein. Furthermore, eachof the embodiments is of the method described above may be performed byany of the systems described herein.

All of the methods described herein may include storing results of oneor more steps of the method embodiments in a non-transitorycomputer-readable storage medium. The results may include any of theresults described herein and may be stored in any manner known in theart. The storage medium may include any storage medium described hereinor any other suitable storage medium known in the art. After the resultshave been stored, the results can be accessed in the storage medium andused by any of the method or system embodiments described herein,formatted for display to a user, used by another software module,method, or system, etc. For example, after the method detects thedefects, the method may include storing information about the detecteddefects in a storage medium.

An additional embodiment relates to a non-transitory computer-readablemedium storing program instructions executable on a computer system forperforming a computer-implemented method for detecting defects on awafer. One such embodiment is shown in FIG. 6. In particular, as shownin FIG. 6, non-transitory computer-readable medium 600 includes programinstructions 602 executable on computer system 404. Thecomputer-implemented method includes the steps of the method describedabove. The computer-implemented method for which the programinstructions are executable may include any other step(s) describedherein.

Program instructions 602 implementing methods such as those describedherein may be stored on computer-readable medium 600. Thecomputer-readable medium may be a storage medium such as a magnetic oroptical disk, a magnetic tape, or any other suitable non-transitorycomputer-readable medium known in the art.

The program instructions may be implemented in any of various ways,including procedure-based techniques, component-based techniques, and/orobject-oriented techniques, among others. For example, the programinstructions may be implemented using ActiveX controls, C++ objects,JavaBeans, Microsoft Foundation Classes (“MCF”), or other technologiesor methodologies, as desired. The program instructions can be run on anyprocessors, such as CPU, GPU etc.

The computer system may take various forms, including a personalcomputer system, image computer, mainframe computer system, workstation,network appliance, Internet appliance, or other device. A computersystem can have a single core or multi-cores. In general, the term“computer system” may be broadly defined to encompass any device havingone or more processors, which executes instructions from a memorymedium. The computer system may also include any suitable processorknown in the art such as a parallel processor. In addition, the computersystem may include a computer platform with high speed processing andsoftware, either as a standalone or a networked tool.

Another embodiment relates to a system configured to detect defects on awafer. One embodiment of such a system is shown in FIG. 7. The systemincludes an inspection subsystem configured to acquire information for atarget on a wafer. The inspection subsystem may include any suitableinspection subsystem such as an e-beam inspection (EBI) or electron beamreview (EBR) subsystem. Examples of suitable EBI subsystems includethose that are included in commercially available FBI tools such as theeSxxx tools from KLA-Tencor, Milpitas, Calif., and tools from othersuppliers such as Hermes Microvision, Inc., Hsinchu City, Taiwan, or NGRInc., Yokohama, Japan, Electron beam subsystems can collect images inmultiple modes, and the images can be used either in a die-to-diecomparison, a cell-to-cell comparison, or a die-to-database comparison.Alternatively, the inspection subsystem may include an opticalinspection subsystem, which may have a configuration as describedherein.

The target includes a POI formed on the wafer and a known DOI occurringproximate to or in the POI. The target may be further configured asdescribed herein. The information includes a first image of the POI onthe wafer acquired by imaging the POI on the wafer with a first channelof the inspection subsystem and a second image of the known DOI on thewafer acquired by imaging the known DOI with a second channel of theinspection subsystem. The image of the target may include any suitabledata, image data, signals or image signals. The inspection subsystem mayimage the target on the wafer in any suitable manner. The informationfor the target may include any other target information describedherein.

The inspection subsystem is also configured to search for targetcandidates on the wafer or another wafer. The target candidates includethe POI. The target candidates may be configured as described herein. Asshown in FIG. 7, the inspection subsystem includes light source 702.Light source 702 may include any suitable tight source known in the artsuch as a laser. Light source 702 is configured to direct light to beamsplitter 704, which is configured to reflect the light from tight source702 to refractive optical element 706. Refractive optical element 706 isconfigured to focus light from beam splitter 704 to wafer 708. Beamsplitter 704 may include any suitable beam splitter such as a 50/50 beamsplitter. Refractive optical element 706 may include any suitablerefractive optical element, and although refractive optical element 706is shown in FIG. 7 as a single refractive optical element, it may bereplaced with one or more refractive optical elements and/or one or morereflective optical elements.

Light source 702, beam splitter 704, and refractive optical element 706may, therefore, form an illumination channel (referred to herein as the“first illumination channel”) for the inspection subsystem. Theillumination channel may include any other suitable elements (not shownin FIG. 7) such as one or more polarizing components and one or morefitters such as spectral fitters.

As shown in FIG. 7, the light source, beam splitter, and refractiveoptical element are configured such that the light is directed to thewafer at a normal or substantially normal angle of incidence. However,the light may be directed to the wafer at any other suitable angle ofincidence. For example, the inspection subsystem may include a secondillumination channel that is configured to direct tight to the wafer atan oblique angle of incidence. In the embodiment shown in FIG. 7, forexample, the inspection subsystem may also include light source 710 thatis configured generate light and may include any suitable light source.The inspection subsystem may also include refractive optical element 712that is configured to focus light from light source 710 to wafer 708 atan oblique angle of incidence. Therefore, light source 710 andrefractive optical element 712 form another illumination channel for theinspection subsystem. This second illumination channel may also includeany other suitable elements (not shown in FIG. 7) such as thosedescribed above.

In the embodiment shown in FIG. 7, therefore, the inspection subsystemmay include two different light sources that are included in twodifferent illumination channels. The two different light sources mayhave the same configuration or different configurations. For example,the light sources may be different lasers having differentconfigurations. In addition, the light sources may generate light havingthe same characteristics or one or more different characteristics. Inone such example, the light generated by the different light sources mayhave different wavelengths and/or different polarizations. Furthermore,the inspection subsystem may include only one light source in place ofthe two shown in FIG. 7 and the light from the light source may be splitinto two different beams that are used by two different channels forillumination of the wafer.

The inspection subsystem may be configured to scan the light over thewale/any suitable manner.

Light reflected from wafer 708 due to illumination by the firstillumination channel described above may be collected by refractiveoptical element 706 and may be directed through beam splitter 704, andpossibly beam splitter 714, to detector 716. Therefore, the refractiveoptical element, beam splitters, and detector may form a detectionchannel (also referred to herein as the “first detection channel”) ofthe inspection subsystem. The detector may include any suitable imagingdetector known in the art such as a charge coupled device (CCD). Thisdetection channel may also include one or more additional components(not shown in FIG. 7) such as one or more polarizing components, one ormore spatial filters, one or more spectral filters, and the like.Detector 716 is configured to generate an image that is responsive tothe reflected light detected by the detector.

As shown in FIG. 7, the first illumination channel is configured todirect light to the wafer through the same refractive optical elementused for collecting tight from the wafer. Therefore, the firstillumination channel; as shown in FIG. 7, is configured as a“through-the-lens” illumination channel. In addition, since the secondillumination channel does not direct light to the wafer through therefractive optical element that is used for collecting light from thewafer, the second illumination channel is configured as an“outside-the-lens” illumination channel. The inspection subsystem mayinclude any suitable one or more “through-the-lens” illuminationchannels and/or one or more “outside-the-lens” illumination channels.

Light reflected from wafer 708 due to illumination by the firstillumination channel described above that is collected by refractiveoptical element 706 may also be directed through beam splitter 704 tobeam splitter 714 that reflects at least a portion of the collectedlight to detectors 718 and 720. Therefore, the refractive opticalelement, beam splitters, and detector 718 may form a detection channel(also referred to herein as the “second detection channel”) of theinspection subsystem, and the refractive optical element, beamsplitters, and detector 720 may form a detection channel (also referredto herein as the “third detection channel”) of the inspection subsystem.The detectors and their respective detection channels may be furtherconfigured as described above. In some instances, the inspectionsubsystem may be configured such that light from beam splitter 714 isdirected to only one detector (not shown in FIG. 7), which may beconfigured as described above.

As described above, each of the detectors included in the inspectionsubsystem may be configured to detect light reflected from the wafer.Therefore, each of the detection channels included in the inspectionsubsystem may be configured as Bright-Field channels. However, one ormore of the detection channels may be used to detect light scatteredfrom the wafer due to illumination by one or more of the illuminationchannels. For instance, in the embodiment shown in FIG. 7, detector 716may be used to detect light reflected from the wafer due to illuminationby the first illumination channel, and detectors 718 and 720 may be usedto detect light scattered from the wafer due to illumination by thesecond illumination channel. In another example, detectors 716, 718, 720may each be used to detect light reflected from the wafer due toillumination by the first illumination channel, the illumination channelused for illumination of the wafer may be switched, and each of thedetectors may then be used to detect light scattered from the wafer dueto illumination by the second channel. The illumination channel used forillumination of the wafer may be switched in any suitable manner (e.g.,by manipulation of one or more shutters (not shown in FIG. 7), which maybe included in one or more of the illumination channels). Imagesacquired through any channel can be used for POI search or defectdetection.

Furthermore, although the inspection subsystem is shown in FIG. 7 asincluding one collection lens (i.e., refractive optical element 706)that collects the light that is detected by all of the detectors (andtherefore all of the channels) of the inspection subsystem, theinspection subsystem may include more than one collection lens, and oneor more detectors may be used to detect the light collected by eachcollection lens. In this manner, collections optics may be separate forthe various channels.

The system also includes computer system 722 configured to detect theknown DOI in the target candidates by identifying potential DOIlocations based on images of the target candidates acquired by the firstchannel and applying one or more detection parameters to images acquiredby the second channel of the potential DOI locations. The computersystem may identify the locations and apply the one or more detectionparameters as described further herein. In addition, the computer systemmay be configured to perform any other step(s) described herein.

Images generated by all of the detectors included in each of thedetection channels of the inspection subsystem may be provided tocomputer system 722. For example, the computer system may be coupled tothe detectors (e.g., by one or more transmission is media shown by thedashed lines in FIG. 7, which may include any suitable transmissionmedia known in the art) such that the computer system may receive theimages generated by the detectors. The computer system may be coupled tothe detectors in any suitable manner. The computer system may be furtherconfigured as described herein. The inspection subsystem may also befurther configured as described herein. Furthermore, the system may befurther configured as described herein.

As noted above, a key part of the embodiments is acquiring multipleimages of the same location on a wafer through more than one channel,simultaneously or sequentially, from different perspectives, withdifferent spectra (i.e., wavelength bands), apertures, polarizations,imaging mechanisms, or some combination thereof. Some images may bebetter for pattern resolution while some are better for defectdetection.

Multiple images may be collected simultaneously through separatemultiple channels in the same inspection system such as that describedabove or using two channels (e.g., Channel 1 and Channel 2) of aDark-Field system like Puma 9650 that is commercially available fromKLA-Tencor. Alternatively, multiple images may be collected sequentially(i.e., multi-pass) on either a multi-channel system (e.g., Channel 1 andChannel 2 of Puma performed in a multi-pass scenario with two differentpolarizations) or a single-channel system (e.g., Vanquish with twodifferent apertures or a single channel on a multi-channel system suchas Puma). The two or more channels used in the embodiments describedherein may also include two or more collection channels configured fordifferent ranges of numerical aperture (e.g., as in the Puma system).Obviously, many combinations of channels with many combinations ofconfigurations can be used in the embodiments described herein.

Various inspection architectures offered by KLA-Tencor and othercompanies can be used to implement the embodiments described hereinincluding the line-illumination architecture on KLA-Tencor's Puma, thespot-illumination architecture on UV-Vision, which is commerciallyavailable from Applied Materials, Inc., Santa Clara, Calif., and theflood-illumination architectures on patterned inspection systems fromHitachi High Technologies America, Inc., Pleasanton, Calif., andNegevtech Ltd., Santa Clara, Calif. Some of these systems, e.g., thosefrom Hitachi and Negevtech, originally use a single channel and can beadapted to add one or more additional channels, which would allow themto collect multiple images in one pass or multiple passes. Some of thesesystems, e.g., Applied Materials' UV-Vision, already have multiplechannels, e.g., BF and DF channels, so they could collect multipleimages in one pass or multiple passes. Applied. Materials' DF systemssuch as ComPlus, Sting, and DFinder all have multiple channels as well.All of these wafer inspection systems and architectures, from KLA-Tencorand other companies, can be used with the multi-image embodimentsdescribed herein.

In some embodiments such as that shown in FIG. 7, the system may usethrough-the-lens illumination and that illumination can be single spot,multi-spot, flood, or line illumination, in addition, any suchillumination configurations may be used with separate and simultaneousBF and DF (or gray-field (GF)) collection. For example, as describedabove with respect to FIG. 7, the light from the wafer due toillumination by the first illumination channel can be collected anddetected by multiple channels, each of which may be configured to detectreflected light (as in a BF configuration) or scattered light (as in aDF configuration). In some such configurations, the illumination may bedirected through only a portion of the lens (i.e., refractive opticalelement 706) or collection optics, while different portions of the NA ofthat lens or collection optics may be used for only DF or BF detection.In other words, the inspection subsystem may be configured such thatlight in a first portion of the collection NA is directed to only somedetectors of the inspection subsystem while light in a second portion ofthe collection NA is directed to only some other detectors of theinspection subsystem. Therefore, different portions of the collection NAmay be detected mutually exclusively by different detection channels ofthe inspection subsystem.

In one such embodiment shown in FIG. 8, through-the-lens illuminationmay be performed by directing light through portion 800 of collection NA802. For example, in the embodiment shown in FIG. 8, beam splitter 704shown in FIG. 7 may be configured to direct light from light source 702through only portion 800 of the collection NA. In one such embodiment,as shown in FIG. 8, the light from the wafer in portion 804 of thecollection NA may be directed to only one or more BF channels whilelight in portion 806 of the collection NA may be directed to only one ormore DF channels. For example, in one such embodiment, substantially allof the light in portion 804 of the collection NA may be allowed to passthrough beam splitters 704 and 714 of the system shown in FIG. 7 to oneor more BF channels (e.g., the detection channel that includes detector716) while substantially all of the light in portion 806 shown in FIG. 8may be transmitted by beam splitter 704 and reflected by beam splitter714 to one or more DF channels (e.g., one or more of the detectionchannels that include detectors 718 and 720 shown in FIG. 7). In onesuch embodiment, beam splitter 714 may be configured to have asubstantially transmissive central portion that corresponds to portion804 of the collection NA and a substantially reflective outer, annularportion that corresponds to portion 806 of the collection NA. Therefore,the light detected by the BF channel(s) is mutually exclusive of thelight detected by the DF channel(s) and vice versa. (The double-headedarrows shown in FIG. 8 indicate that the boundaries of the illuminationand collection NAs are arbitrary.)

In some embodiments such as that shown in FIG. 7, the system may useoutside-the-lens illumination and that illumination can be single spot,multi-spot, flood, or line illumination. In addition, any suchillumination configurations may be used with multiple DF collectionchannels. In this manner, any such illumination configurations may beused with separate and simultaneous multi-DF collection. For example, asdescribed above with respect to FIG. 7, the light from the wafer due toillumination by the second illumination channel can be collected anddetected by multiple channels, each of which may be configured to detectscattered light (as in a DF configuration). In some such configurations,different portions of the NA of the lens (i.e., refractive opticalelement 706) may be used for only corresponding, different DF detection.In other words, the inspection subsystem may be configured such thatscattered light in a first portion of the collection NA is directed toonly some detector(s) of the inspection subsystem, scattered light in asecond portion of the collection NA is directed to only some otherdetector(s) of the inspection subsystem, etc. Therefore, differentportions of the collection NA may be detected and used mutuallyexclusively by different DF detection channels of the inspectionsubsystem.

In one such embodiment shown in FIG. 9, outside-the-lens illuminationmay be performed by directing light to an area on the wafercorresponding to portion 900 of collection space 902 of the inspectionsubsystem. For example, in the embodiment shown in FIG. 9, refractiveoptical element 712 of the system shown in FIG. 7 may be configured todirect light from light source 710 to an area on wafer 708 correspondingto portion 900 of the collection space. In one such embodiment, thescattered light from the wafer in portion 904 of the collection spacemay be directed to only a first DF channel, while scattered light inportion 906 of the collection space may be directed to only a second DFchannel and scattered light in portion 908 of collection space 902 maybe directed to only a third DF channel. For example, with reference tothe embodiment shown in FIG. 7, substantially all of the light inportion 904 of the collection space may be reflected by beam splitter714 to detector 718, substantially all of the light in portion 906 ofthe collection space may be transmitted by beam splitter 714 to detector716, and substantially all of the light in portion 908 of the collectionspace may be reflected by beam splitter 714 to detector 720. In thisconfiguration, each of the detectors shown in FIG. 7 may be used forscattered light detection. In this manner, each of the detectionchannels shown in FIG. 7 may be used as DF channels. In one suchembodiment, beam splitter 714 may be configured to have a substantiallytransmissive central portion that corresponds to portion 906 of thecollection space and substantially reflective outer portions thatcorrespond to portions 904 and 908 of the collection space. Therefore,the light detected by each of the DF channel(s) is mutually exclusive ofthe light detected by each other DF channel(s) and vice versa. (Thedouble-headed arrows shown in FIG. 9 indicate that the boundaries of theillumination and collection NAs are arbitrary.)

It is noted that FIG. 7 is provided herein to generally illustrate oneconfiguration of an inspection subsystem that may be included in thesystem embodiments described herein. Obviously, the inspection subsystemconfiguration described herein may be altered to optimize theperformance of the inspection system as is normally performed whendesigning a commercial inspection system. In addition, the systemsdescribed herein may be implemented using an existing inspection system(e.g., by adding functionality described herein to an existinginspection system) such as the 28XX, 29XX, and Puma 9XXX series of toolsthat are commercially available from KLA-Tencor and any of the othercommercially available tools noted above. For some such systems, themethods described herein may be provided as optional functionality ofthe system (e.g., in addition to other functionality of the system).Alternatively, the system described herein may be designed “fromscratch” to provide a completely new system.

Further modifications and alternative embodiments of various aspects ofthe invention will be apparent to those skilled in the art in view ofthis description. For example, methods and systems for detecting defectson a wafer are provided. Accordingly, this description is to beconstrued as illustrative only and is for the purpose of teaching thoseskilled in the art the general manner of carrying out the invention. Itis to be understood that the forms of the invention shown and describedherein are to be taken as the presently preferred embodiments. Elementsand materials may be substituted for those illustrated and describedherein, parts and processes may be reversed, and certain features of theinvention may be utilized independently, all as would be apparent to oneskilled in the art after having the benefit of this description of theinvention. Changes may be made in the elements described herein withoutdeparting from the spirit and scope of the invention as described in thefollowing claims.

What is claimed is:
 1. A computer-implemented method for detecting defects on a wafer, comprising: acquiring information for a target on a wafer, wherein the target comprises a pattern of interest formed on the wafer and a known defect of interest occurring proximate to or in the pattern of interest, and wherein the information comprises a first image of the pattern of interest on the wafer acquired by imaging the pattern of interest on the wafer with a first channel of an inspection system, a second image of the known defect of interest on the wafer acquired by imaging the known defect of interest with a second channel of the inspection system, a location of the pattern of interest on the wafer, a location of the known defect of interest relative to the pattern of interest, and one or more characteristics computed from the pattern of interest and the known defect of interest; searching for target candidates within one die on the wafer, or on another wafer, wherein the target candidates comprise the pattern of interest; and detecting the known defect of interest in the target candidates by identifying potential defect of interest locations based on images of the target candidates acquired by the first channel and applying one or more detection parameters to images acquired by the second channel of the potential defect of interest locations, wherein said detecting is performed using a computer system.
 2. The method of claim 1, wherein design data for the wafer or the other wafer is not required for any step of the method.
 3. The method of claim 1, wherein the location of the known defect of interest is obtained based on design data for the wafer.
 4. The method of claim 1, wherein the location of the known defect of interest is obtained based on optical images or scanning electron microscope images of the wafer.
 5. The method of claim 1, further comprising determining the location of the known defect of interest in an optical image of the wafer by correlating a scanning electron microscope image of the known defect of interest to the optical image of the wafer.
 6. The method of claim 1, wherein acquiring the information for the target comprises grabbing images of the target on the wafer with multiple channels of the inspection system, and wherein the multiple channels comprise at least the first channel and the second channel.
 7. The method of claim 1, wherein acquiring the information for the target comprises grabbing images of the pattern of interest with multiple channels of the inspection system, determining which of the grabbed images is best for pattern searching, and designating one of the multiple channels with which the best of the grabbed images for the pattern searching was grabbed as the first channel.
 8. The method of claim 1, wherein acquiring the information for the target comprises generating additional images of the wafer at and proximate to the known defect of interest with multiple channels of the inspection system, determining which of the additional images is best for pattern searching, and selecting the pattern of interest from the additional image that is determined to be the best for the pattern searching.
 9. The method of claim 1, wherein acquiring the information for the target comprises grabbing images of the known defect of interest with multiple channels of the inspection system, determining which of the grabbed images is best for said detecting, and designating one of the multiple channels with which the best of the grabbed images was grabbed as the second channel.
 10. The method of claim 1, wherein acquiring the information for the target comprises specifying size, shape and location of care areas, size, shape and location of templates, and area where the one or more characteristics are determined in the images to which the one or more detection parameters are applied.
 11. The method of claim 1, wherein acquiring the information for the target comprises grabbing templates for all known defects of interest in one die, on the wafer or the other wafer, in which said searching is performed with at least the first channel of the inspection system.
 12. The method of claim 1, wherein acquiring the information for the target comprises determining a similarity between a template for the pattern of interest and an image of the target acquired by imaging the target on the wafer with the first channel and determining a uniqueness of the pattern of interest relative to other patterns proximate to the pattern of interest.
 13. The method of claim 1, wherein the pattern of interest has a width and a height that are shorter than a width and a height, respectively, of dies formed on the wafer and the other wafer.
 14. The method of claim 1, wherein the one or more characteristics comprise size, shape, intensity, contrast, or polarity of the known defect of interest.
 15. The method of claim 1, wherein the one or more characteristics comprise one or more characteristics of the known defect of interest determined from the second image acquired with the second channel.
 16. The method of claim 1, wherein the location of the known defect of interest is unique relative to the location of the pattern of interest.
 17. The method of claim 1, wherein micro care areas are generated to cover one or more of the potential defect of interest locations.
 18. The method of claim 1, wherein said acquiring and said searching are performed with the inspection system in a setup step before defect detection.
 19. The method of claim 1, wherein said acquiring and said searching are performed with a different inspection system of the same type as the inspection system.
 20. The method of claim 1, wherein said acquiring and said searching are performed in different dies on the wafer or the other wafer, and wherein said searching is performed in one die on the wafer or the other wafer using one or more templates for the target candidates.
 21. The method of claim 1, further comprising determining one or more parameters of a care area based on results of said searching.
 22. The method of claim 1, further comprising determining a care area location by correlating a template image for the pattern of interest and the images for the target candidates acquired by the first channel and applying the care area location to the images acquired by the second channel of the potential defect of interest locations.
 23. The method of claim 1, further comprising selecting one or more characteristics of the target, selecting the one or more detection parameters, and determining one or more parameters of a care area such that defects other than the known defect of interest are not detected in the target candidates.
 24. The method of claim 1, further comprising creating a template for the pattern of interest and modifying the template by changing the size of the template or flipping, rotating, or processing the template.
 25. The method of claim 1, wherein the first channel, at least in part, defines the best optics mode for image matching of the images of the target candidates to the first image or a template for the pattern of interest.
 26. The method of claim 1, further comprising determining the one or more detection parameters based on the information for the target.
 27. The method of claim 1, wherein the inspection system uses different optics modes in the first and second channels, and wherein the different optics modes are defined by spectrum, aperture, polarization, or some combination thereof.
 28. The method of claim 1, wherein the images acquired by the first and second channels are spatially registered to each other by image sensor calibration and alignment algorithms applied on the images.
 29. A non-transitory computer-readable medium, storing program instructions executable on a computer system for performing a computer-implemented method for detecting defects on a wafer, wherein the computer-implemented method comprises: acquiring information for a target on a wafer, wherein the target comprises a pattern of interest formed on the wafer and a known defect of interest occurring proximate to or in the pattern of interest, and wherein the information comprises a first image of the pattern of interest on the wafer acquired by imaging the pattern of interest on the wafer with a first channel of an inspection system, a second image of the known defect of interest on the wafer acquired by imaging the known defect of interest with a second channel of the inspection system, a location of the pattern of interest on the wafer, a location of the known defect of interest relative to the pattern of interest, and one or more characteristics computed from the pattern of interest and the known defect of interest; searching for target candidates in one die on the wafer or on another wafer, wherein the target candidates comprise the pattern or interest; and detecting the known defect of interest in the target candidates by identifying potential defect of interest locations based on images of the target candidates acquired by the first channel and applying one or more detection parameters to images acquired by the second channel of the potential defect of interest locations.
 30. A system configured to detect defects on a wafer, comprising: an inspection subsystem configured to acquire information for a target on a wafer, wherein the target comprises a pattern of interest formed on the wafer and a known defect of interest occurring proximate to or in the pattern of interest, and wherein the information comprises a first image of the pattern of interest on the wafer acquired by imaging the pattern of interest on the wafer with a first channel of the inspection subsystem and a second image of the known defect of interest on the wafer acquired by imaging the known defect of interest with a second channel of the inspection subsystem; wherein the inspection subsystem is further configured to search for target candidates in one die on the wafer or on another wafer, wherein the target candidates comprise the pattern of interest; and a computer system configured to detect the known defect of interest in the target candidates by identifying potential defect of interest locations based on images of the target candidates acquired by the first channel and applying one or more detection parameters to images acquired by the second channel of the potential defect of interest locations. 